There is considerable interest in identifying and/or measuring the receipt of, and or exposure to, audio data by an audience in order to provide market information to advertisers, media distributors, and the like, to verify airing, to calculate royalties, to detect piracy, and for any other purposes for which an estimation of audience receipt or exposure is desired.
The emergence of multiple, overlapping media distribution pathways, as well as the wide variety of available user systems (e.g. PC's, PDA's, portable CD players, Internet, appliances, TV, radio, etc.) for receiving audio data, has greatly complicated the task of measuring audience receipt of, and exposure to, individual program segments. The development of commercially viable techniques for encoding audio data with program identification data provides a crucial tool for measuring audio data receipt and exposure across multiple media distribution pathways and user systems.
One such technique involves adding an ancillary code to the audio data that uniquely identifies the program signal. Most notable among these techniques is the methodology developed by Arbitron Inc., which is already providing useful audience estimates to numerous media distributors and advertisers.
An alternative technique for identifying program signals is extraction and subsequent pattern matching of “signatures” of the program signals. Such techniques typically involve the use of a reference signature database, which contains a reference signature for each program signal the receipt of which, and exposure to which, is to be measured. Before the program signal is broadcast, these reference signatures are created by measuring the values of certain features of the program signal and forming a feature set or “signature” from these values, commonly termed “signature extraction”, which is then stored in the database. Later, when the program signal is broadcast, signature extraction is again performed, and the signature obtained is compared to the reference signatures in the database until a match is found and the program signal is thereby identified.
However, one disadvantage of using such pattern matching techniques is that, after a signature is extracted from a program signal, the signature must be compared to numerous reference signatures in the database until a match is found. This problem is further exacerbated in systems that do not use a “cue” or “start” code to trigger the extraction of the signature at a particular predetermined point in the program signal, as such systems require the program signal to continually undergo signature extraction, and each of these many successive signatures extracted from a single program signal must be compared to each and every reference signature in the database until a match is found. This, of course, requires a tremendous amount of data processing, which, due to the ever increasing methods and amounts of audio data transmission, is becoming more and more economically impractical.
Accordingly, it is desired to provide techniques for gathering data reflecting receipt of and/or exposure to audio data that require minimal processing and storage resources.
It is also desired to provide such data gathering techniques which are likely to be adaptable to future media distribution paths and user systems.